RNA-Seq data analysis has become vital to understanding gene structure and expression patterns in transcriptomic studies. A typical reference genome guided RNA-Seq workflow involves the following steps: quality control of reads, alignment of reads to reference genomes, assembly of reads, quantification, differential expression, and visualization. The current ecosystem of RNA-Seq tools and protocols is vast and diverse. The performance of these tools varies across computing platforms, and hence it becomes critical to choose an analysis protocol that is scalable and accurate when handling large datasets on different computing platforms.
In this webinar, we will demonstrate the updated Tuxedo protocols HISAT2, StringTie, and Ballgown, which align the sequencing reads to a reference genome determining its gene structure quality and differential gene expression patterns between experimental conditions. We will also demo another RNA-Seq quantification workflow, Kallisto and Sleuth, which relies on pseudo alignment of reads to a reference transcriptome. This second approach shows significant improvement in performance compared with the alignment-based methods in the first approach. This webinar will demo both workflows and the visualization of downstream results using CyVerse Cyberinfrastructure. The reference tutorials (not required for attendance) for this webinar are online at: https://wiki.cyverse.org/wiki/display…… and https://wiki.cyverse.org/wiki/display….
CyVerse provides powerful infrastructure for computational research involving large datasets and complex analyses. Using CyVerse, teams can overcome scaling and complexity challenges to tackle questions that previously were unapproachable.